Using Artificial Intelligence to Improve Empathetic Statements in Autistic Adolescents and Adults: A Randomized Clinical Trial.
Four weeks of AI chatbot practice lifted real-world empathetic speech for autistic teens and adults.
01Research in Context
What this study did
Koegel et al. (2025) tested a chatbot named Noora. Noora is an AI that talks like a person.
Autistic teens and adults aged 11-35 used the bot at home for four weeks. They completed 200 short empathy-practice trials.
Half the group started right away. The other half waited. Researchers then compared their real-life conversations.
What they found
The early-start group made far more empathetic statements in everyday talk. The wait-list group did not.
Gains were large and statistically significant. Skills moved from the app to real life.
How this fits with other research
Zhou et al. (2025) pooled 13 earlier tech studies for kids. They found medium benefits for preschoolers using XR and robots. Kern’s new chatbot now shows the same idea works for older clients using words, not pictures.
Kumazaki et al. (2019) used an android to teach job-interview gestures. Kern keeps the robot concept but swaps hardware for software and targets empathy instead of body language.
Brewer et al. (2023) asked autistic adults to pick empathic replies. Most already knew the right answer; they just felt unsure. Kern’s AI gives repeated safe practice, which may boost confidence rather than teach brand-new skills.
Why it matters
You can assign Noora as homework. Ten minutes a night for one month can sharpen empathy without extra clinic time. Try it while you run other programs.
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02At a glance
03Original abstract
Challenges with social communication and social interaction are a defining characteristic of autism spectrum disorder (ASD). These challenges frequently interfere with making friendships, securing and maintaining employment, and can lead to co-occurring conditions. While face-to-face clinical interventions with trained professionals can be helpful in improving social conversation, they can be costly and are unavailable to many, particularly given the high prevalence of ASD and lack of professional training. The purpose of this study was to assess whether an AI program using a Large Language Model (LLM) would improve verbal empathetic responses during social conversation. Autistic adolescents and adults, 11-35 years of age, who were able to engage in conversation but demonstrated challenges with empathetic responses participated in this study. A randomized clinical trial design was used to assess the effects of the AI program (Noora) compared to a waitlist control group. Noora asks participants to respond to leading statements and provides feedback on their answers. In this study, participants were asked to respond to 10 statements per day 5 days per week for 4 weeks for an expected total of 200 trials. Pre- and post-intervention conversation samples were collected to assess generalization during natural conversation. Additionally pre- and post-intervention questionnaires regarding each participant's comfort during social conversation and participants' satisfaction with the AI program were collected. The results of this study demonstrated that empathetic responses could be greatly improved by using an AI program for a short period of time. Participants in the experimental group showed statistically significant improvements in empathetic responses, which generalized to social conversation, compared to the waitlist control group. Some participants in the experimental group reported improved confidence in targeted areas and most reported high levels of satisfaction with the program. These findings suggest that AI using LLMs can be used to improve empathetic responses, thereby providing a time- and cost-efficient support program for improving social conversation in autistic adolescents and adults.
Journal of autism and developmental disorders, 2025 · doi:10.1017/iop.2022.95